The Population Divergence and Genetic Basis of Local Adaptation of Wild Soybean (Glycine soja) in China.

Glycine soja is the wild relative species of cultivated soybean. In this study, we investigated the population divergence and genetic basis of the local adaptation of wild soybean in China using genome-wide single-nucleotide polymorphisms (SNPs) of a population of 72 G. soja accessions. Using phylogenetic analysis, we observed that G. soja accessions clustered into three distinct groups, each corresponding to a specific geographic region, the northeastern region (NER), central region (CR), and southern region (SR), consistent with previous studies. Notably, we found a significant positive correlation between genetic and geographic distances. Further population structure analysis revealed each group was associated with an ancestral population and a specific geographic area. By utilizing the genome sequencing data of accessions from 16 different locations, we inferred the population history of these wild soybean groups. Our results indicate that the three groups diverged ~25,000 years ago, coinciding with the time of the last glacial maximum. The effective population size of the SR group expanded first, and subsequently, the NER and CR groups expanded approximately 5000 and 2500 years ago, respectively. Moreover, 83, 104, and 101 significant associated loci (SALs) were identified using genome-wide association analysis for annual mean temperature, annual precipitation, and latitude, respectively. Functional analysis of genes located in SALs highlighted candidate genes related to local adaptation. This study highlights the significant role of geographic isolation and environmental factors in shaping the genetic structure and adaptability of wild soybean populations. Furthermore, it emphasizes the value of wild soybean as a crucial genetic resource for enhancing the adaptability of cultivated soybeans, which have experienced a loss of genetic diversity due to domestication and intensive breeding practices. The insights gained from our research provide valuable information for the protection, conservation, and utilization of this important genetic resource.

Flavonoid Biosynthesis Pathway May Indirectly Affect Outcrossing Rate of Cytoplasmic Male-Sterile Lines of Soybean.

(1) Background: Cytoplasmic male sterility (CMS) is important for exploiting heterosis. Soybean (Glycine max L.) has a low outcrossing rate that is detrimental for breeding sterile lines and producing hybrid seeds. Therefore, the molecular mechanism controlling the outcrossing rate should be elucidated to increase the outcrossing rate of soybean CMS lines; (2) Methods: The male-sterile soybean lines JLCMS313A (with a high outcrossing rate; HL) and JLCMS226A (with a low outcrossing rate; LL) were used for a combined analysis of the transcriptome (RNA-seq) and the targeted phenol metabolome; (3) Results: The comparison between HL and LL detected 5946 differentially expressed genes (DEGs) and 81 phenolic metabolites. The analysis of the DEGs and differentially abundant phenolic metabolites identified only one common KEGG pathway related to flavonoid biosynthesis. The qRT-PCR expression for eight DEGs was almost consistent with the transcriptome data. The comparison of the cloned coding sequence (CDS) regions of the SUS, FLS, UGT, and F3H genes between HL and LL revealed seven single nucleotide polymorphisms (SNPs) only in the F3H CDS. Moreover, five significant differentially abundant phenolic metabolites between HL and LL were associated with flavonoid metabolic pathways. Finally, on the basis of the SNPs in the F3H CDS, one derived cleaved amplified polymorphic sequence (dCAPS) marker was developed to distinguish between HL and LL soybean lines; (4) Conclusions: The flavonoid biosynthesis pathway may indirectly affect the outcrossing rate of CMS sterile lines in soybean.

Whole-body tumor segmentation from PET/CT images using a two-stage cascaded neural network with camouflaged object detection mechanisms.

BACKGROUND: Whole-body Metabolic Tumor Volume (MTVwb) is an independent prognostic factor for overall survival in lung cancer patients. Automatic segmentation methods have been proposed for MTV calculation. Nevertheless, most of existing methods for patients with lung cancer only segment tumors in the thoracic region. PURPOSE: In this paper, we present a Two-Stage cascaded neural network integrated with Camouflaged Object Detection mEchanisms (TS-Code-Net) for automatic segmenting tumors from whole-body PET/CT images. METHODS: Firstly, tumors are detected from the Maximum Intensity Projection (MIP) images of PET/CT scans, and tumors' approximate localizations along z-axis are identified. Secondly, the segmentations are performed on PET/CT slices that contain tumors identified by the first step. Camouflaged object detection mechanisms are utilized to distinguish the tumors from their surrounding regions that have similar Standard Uptake Values (SUV) and texture appearance. Finally, the TS-Code-Net is trained by minimizing the total loss that incorporates the segmentation accuracy loss and the class imbalance loss. RESULTS: The performance of the TS-Code-Net is tested on a whole-body PET/CT image data-set including 480 Non-Small Cell Lung Cancer (NSCLC) patients with five-fold cross-validation using image segmentation metrics. Our method achieves 0.70, 0.76, and 0.70, for Dice, Sensitivity and Precision, respectively, which demonstrates the superiority of the TS-Code-Net over several existing methods related to metastatic lung cancer segmentation from whole-body PET/CT images. CONCLUSIONS: The proposed TS-Code-Net is effective for whole-body tumor segmentation of PET/CT images. Codes for TS-Code-Net are available at: https://github.com/zyj19/TS-Code-Net.

Mutation of GmAITR Genes by CRISPR/Cas9 Genome Editing Results in Enhanced Salinity Stress Tolerance in Soybean.

Breeding of stress-tolerant plants is able to improve crop yield under stress conditions, whereas CRISPR/Cas9 genome editing has been shown to be an efficient way for molecular breeding to improve agronomic traits including stress tolerance in crops. However, genes can be targeted for genome editing to enhance crop abiotic stress tolerance remained largely unidentified. We have previously identified abscisic acid (ABA)-induced transcription repressors (AITRs) as a novel family of transcription factors that are involved in the regulation of ABA signaling, and we found that knockout of the entire family of AITR genes in Arabidopsis enhanced drought and salinity tolerance without fitness costs. Considering that AITRs are conserved in angiosperms, AITRs in crops may be targeted for genome editing to improve abiotic stress tolerance. We report here that mutation of GmAITR genes by CRISPR/Cas9 genome editing leads to enhanced salinity tolerance in soybean. By using quantitative RT-PCR analysis, we found that the expression levels of GmAITRs were increased in response to ABA and salt treatments. Transfection assays in soybean protoplasts show that GmAITRs are nucleus proteins, and have transcriptional repression activities. By using CRISPR/Cas9 to target the six GmAITRs simultaneously, we successfully generated Cas9-free gmaitr36 double and gmaitr23456 quintuple mutants. We found that ABA sensitivity in these mutants was increased. Consistent with this, ABA responses of some ABA signaling key regulator genes in the gmaitr mutants were altered. In both seed germination and seedling growth assays, the gmaitr mutants showed enhanced salt tolerance. Most importantly, enhanced salinity tolerance in the mutant plants was also observed in the field experiments. These results suggest that mutation of GmAITR genes by CRISPR/Cas9 is an efficient way to improve salinity tolerance in soybean.

MicroRNAs Involved in Regulatory Cytoplasmic Male Sterility by Analysis RNA-seq and Small RNA-seq in Soybean.

Cytoplasmic male sterility (CMS) is an important plant characteristic for exploiting heterosis to enhance crop traits during breeding. However, the CMS regulatory network remains unclear in plants, even though researchers have attempted to isolate genes associated with CMS. In this study, we performed high-throughput sequencing and degradome analyses to identify microRNAs (miRNAs) and their targets in a soybean CMS line (JLCMS9A) and its maintainer line (JLCMS9B). Additionally, the differentially expressed genes during reproductive development were identified using RNA-seq data. A total of 280 miRNAs matched soybean miRNA sequences in miRBase, including mature miRNAs and pre-miRNAs. Of the 280 miRNAs, 30, 23, and 21 belonged to the miR166, miR156, and miR171 families, respectively. Moreover, 410 novel low-abundant miRNAs were identified in the JLCMS9A and JLCMS9B flower buds. Furthermore, 303 and 462 target genes unique to JLCMS9A and JLCMS9B, respectively, as well as 782 common targets were predicted based on the degradome analysis. Target genes differentially expressed between the CMS line and the maintainer line were revealed by an RNA-seq analysis. Moreover, all target genes were annotated with diverse functions related to biological processes, cellular components, and molecular functions, including transcriptional regulation, the nucleus, meristem maintenance, meristem initiation, cell differentiation, auxin-activated signaling, plant ovule development, and anther development. Finally, a network was built based on the interactions. Analyses of the miRNA, degradome, and transcriptome datasets generated in this study provided a comprehensive overview of the reproductive development of a CMS soybean line. The data presented herein represent useful information for soybean hybrid breeding. Furthermore, the study results indicate that miRNAs might contribute to the soybean CMS regulatory network by modulating the expression of CMS-related genes. These findings lay the foundation for future studies on the molecular mechanisms underlying soybean CMS.

Spatial feature fusion convolutional network for liver and liver tumor segmentation from CT images.

PURPOSE: The accurate segmentation of liver and liver tumors from CT images can assist radiologists in decision-making and treatment planning. The contours of liver and liver tumors are currently obtained by manual labeling, which is time-consuming and subjective. Computer-aided segmentation methods have been widely used in the segmentation of liver and liver tumors. However, due to the diversity of shape, volume, and image intensity, the segmentation is still a difficult task. In this study, we present a Spatial Feature Fusion Convolutional Network (SFF-Net) to automatically segment liver and liver tumors from CT images. METHODS: First, we extract side-outputs at each convolutional block in SFF-Net to make full use of multiscale features. Second, skip-connections are added in the down-sampling phase, therefore, the spatial information can be efficiently transferred to later layers. Third, we present feature fusion blocks (FFBs) to merge spatial features and high-level semantic features from early layers and later layers, respectively. Finally, a fully connected 3D conditional random fields (CRFs) is applied to refine the liver and liver tumor segmentation results. RESULTS: We test our method on the MICCAI 2017 Liver Tumor Segmentation (LiTS) challenge dataset. The Dice Global (DG) score, Dice per case (DC) score, Volume Overlap Error (VOE), Average Symmetric Surface Distance (ASSD), and tumor precision score are calculated to evaluate the liver and liver tumor segmentation accuracies. For the liver segmentation, DG is 0.955; DC is 0.937; VOE is 0.106; and ASSD is 3.678. For the tumor segmentation, DG is 0.746; DC is 0.592; VOE is 0.416; ASSD is 1.585 and the tumor precision score is 0.369. CONCLUSIONS: The SFF-Net learns more spatial information by adding skip-connections and feature fusion blocks. The experiments validate that our method can accurately segment liver and liver tumors from CT images.

Evolution of Homeologous Gene Expression in Polyploid Wheat.

Polyploidization has played a prominent role in the evolutionary history of plants. Two recent and sequential allopolyploidization events have resulted in the formation of wheat species with different ploidies, and which provide a model to study the effects of polyploidization on the evolution of gene expression. In this study, we identified differentially expressed genes (DEGs) between four BBAA tetraploid wheats of three different ploidy backgrounds. DEGs were found to be unevenly distributed among functional categories and duplication modes. We observed more DEGs in the extracted tetraploid wheat (ETW) than in natural tetraploid wheats (TD and TTR13) as compared to a synthetic tetraploid (AT2). Furthermore, DEGs showed higher Ka/Ks ratios than those that did not show expression changes (non-DEGs) between genotypes, indicating DEGs and non-DEGs experienced different selection pressures. For A-B homeolog pairs with DEGs, most of them had only one differentially expressed copy, however, when both copies of a homeolog pair were DEGs, the A and B copies were more likely to be regulated to the same direction. Our results suggest that both cis- and inter-subgenome trans-regulatory changes are important drivers in the evolution of homeologous gene expression in polyploid wheat, with ploidy playing a significant role in the process.

The Effects of Gene Duplication Modes on the Evolution of Regulatory Divergence in Wild and Cultivated Soybean.

Regulatory changes include divergence in both cis-elements and trans-factors, which play roles in organismal evolution. Whole genome duplications (WGD) followed by diploidization are a recurrent feature in the evolutionary history of angiosperms. Prior studies have shown that duplicated genes have different evolutionary fates due to variable selection constraints and results in genomic compositions with hallmarks of paleopolyploidy. The recent sequential WGDs and post-WGD evolution in the common ancestor of cultivated soybean (Glycine max) and wild soybean (Glycine soja), together with other models of gene duplication, have resulted in a highly duplicated genome. In this study, we investigated the transcriptional changes in G. soja and G. max. We identified a sizable proportion of interspecific differentially expressed genes (DEGs) and found parental expression level dominance of G. max in their F1 hybrids. By classifying genes into different regulatory divergence types, we found the trans-regulatory changes played a predominant role in transcriptional divergence between wild and cultivated soybean. The same gene ontology (GO) and protein family (Pfam) terms were found to be over-represented in DEGs and genes of cis-only between JY47 and GS, suggesting the substantial contribution of cis-regulatory divergences to the evolution of wild and cultivated soybeans. By further dissecting genes into five different duplication modes, we found genes in different duplication modes tend to accumulate different types of regulatory differences. A relatively higher proportion of cis-only regulatory divergences was detected in singleton, dispersed, proximal, and tandem duplicates than WGD duplicates and genome-wide level, which is in line with the prediction of gene balance hypothesis for the differential fates of duplicated genes post-WGD. The numbers of cis-only and trans-only regulated genes were similar for singletons, whereas there were more genes of trans-only than cis-only in the rest duplication types, especially in WGD in which there were two times more trans-only genes than that in cis-only type. Tandem duplicates showed the highest proportion of trans-only genes probably due to some special features of this class. In summary, our results demonstrate that genes in different duplication modes have different fates in transcriptional evolution underpinned by cis- or trans-regulatory divergences in soybean and likely in other paleopolyploid higher organisms.

Effects of 3 different residual root treatments after post-and-core restoration: An in vitro fracture resistance experiment and finite element analysis.

STATEMENT OF PROBLEM: Crown-lengthening procedures (CLPs) and orthodontic eruption procedures (OEPs) improve the biomechanical properties of residual root restoration. However, their use is limited by clinic time, cost, and crown-root ratio. An inner shoulder retention form (ISRF) overcomes these limits; however, whether ISRF meets the biomechanical requirements is unclear. PURPOSE: The purpose of this in vitro and finite element analysis (FEA) study was to evaluate the effects of 3 residual root treatments (ISRF, CLP, and OEP) on premolar fracture resistance and stress distribution after post-and-core restoration. MATERIAL AND METHODS: Thirty-two extracted mandibular second premolars were screened and randomly divided into 4 groups (n=8): a 2-mm ferrule restoration group (NPR2; control group) and 3 experimental groups (0.5×0.5-mm ISRF [ISRF0.5], 2-mm CLP [CLP2], and 2-mm OEP [OEP2]). After removal of the crown, endodontic treatment, and embedding and restoration, the specimens were loaded on a universal tester (crosshead speed of 0.1 mm per minute) at 30 degrees to the long axis of the tooth until fracture. Fracture resistance and pattern were analyzed. Four groups were added in FEA: 1-mm ferrule restoration group (NPR1), 1.0×1.0-mm ISRF (ISRF1), 1-mm CLP (CLP1), and 1-mm OEP (OEP1). The maximum principal stress peak (σmax), maximum displacement, and stress distribution were evaluated. RESULTS: Mean fracture load ±standard deviation was 796.23 ±155.61 N (NPR2), 650.32 ±150.43 N (ISRF0.5), 385.38 ±149.92 N (CLP2), and 542.93 ±79.34 N (OEP2); these differences were statistically significant (F=12.724; P<.001). The main fracture patterns were decementation from the lingual crown margin and oblique root fracture in ferrule restoration groups and post-and-core decementation and oblique fracture starting from the middle proximal surface in the ISRF groups without ferrules. In FEA, the results of NPR2, ISRF0.5, CLP2, and OEP2 were consistent with the in vitro experiments and provided stress distribution and displacement information. CONCLUSIONS: Teeth with crown dentin ferrules showed higher fracture resistance and lower stress concentration. For residual roots, ISRF and OEP showed no differences, but CLP had lower fracture resistance and higher stress concentration.

Cytoplasm Types Affect DNA Methylation among Different Cytoplasmic Male Sterility Lines and Their Maintainer Line in Soybean (Glycine max L.).

Cytoplasmic male sterility (CMS) lines and their maintainer line have the same nucleus but different cytoplasm types. We used three soybean (Glycine max L.) CMS lines, JLCMS9A, JLCMSZ9A, and JLCMSPI9A, and their maintainer line, JLCMS9B, to explore whether methylation levels differed in their nuclei. Whole-genome bisulfite sequencing of these four lines was performed. The results show that the cytosine methylation level in the maintainer line was lower than in the CMS lines. Compared with JLCMS9B, the Gene Ontology (GO) enrichment analysis of DMR (differentially methylated region, DMR)-related genes of JLCMS9A revealed that their different 5-methylcytosine backgrounds were enriched in molecular function, whereas JLCMSZ9A and JLCMSPI9A were enriched in biological process and cellular component. The Kyoto Encyclopedia of Genes and Genome (KEGG) analysis of DMR-related genes and different methylated promoter regions in different cytosine contexts, hypomethylation or hypermethylation, showed that the numbers of DMR-related genes and promoter regions were clearly different. According to the DNA methylation and genetic distances separately, JLCMS9A clustered with JLCMS9B, and JLCMSPI9A with JLCMSZ9A. Thus, the effects of different cytoplasm types on DNA methylation were significantly different. This may be related to their genetic distances revealed by re-sequencing these lines. The detected DMR-related genes and pathways that are probably associated with CMS are also discussed.

Comparative transcriptome analysis of flower heterosis in two soybean F1 hybrids by RNA-seq.

Heterosis has been widely exploited as an approach to enhance crop traits during breeding. However, its underlying molecular genetic mechanisms remain unclear. Recent advances in RNA sequencing technology (RNA-seq) have provided an opportunity to conduct transcriptome profiling for heterosis studies. We used RNA-seq to analyze the flower transcriptomes of two F1 hybrid soybeans (HYBSOY-1 and HYBSOY-5) and their parents. More than 385 million high-quality reads were generated and aligned against the soybean reference genome. A total of 681 and 899 genes were identified as being differentially expressed between HYBSOY-1 and HYBSOY-5 and their parents, respectively. These differentially expressed genes (DEGs) were categorized into four major expression categories with 12 expression patterns. Furthermore, gene ontology (GO) term analysis showed that the DEGs were enriched in the categories metabolic process and catalytic activity, while Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis found that metabolic pathway and biosynthesis of secondary metabolites were enriched in the two F1 hybrids. Comparing the DEGs of the two F1 hybrids by GO term and KEGG pathway analyses identified 26 common DEGs that showed transgressive up-regulation, and which could be considered potential candidate genes for heterosis in soybean F1 hybrids. This identification of an extensive transcriptome dataset gives a comprehensive overview of the flower transcriptomes in two F1 hybrids, and provides useful information for soybean hybrid breeding. These findings lay the foundation for future studies on molecular mechanisms underlying soybean heterosis.